Automatic Performance Analysis for CRAY T3E

One of the reasons why parallel programming is considered to be a difficult task is that users frequently cannot predict the performance impact of implementation decisions prior to program execution. This results in a cycle of incremental performance improvements based on runtime performance data. While gathering and analyzing performance data is supported by a large number of tools, typically interactive, the task of performance analysis is still too complex for users. This article illustrates this fact based on the current analysis support on CRAY T3E. As a consequence, we are convinced that automatic analysis tools are required to identify frequently occuring and well-defined performance problems automatically. This article describes the novel design of a generic automatic performance analysis environment called KOJAK. Besides its structure we also outline the first component, EARL, a new meta-tool designed and implemented as a programmable interface to calculate more abstract metrics from existing trace files, and to locate complex patterns describing performance problems